ENHANCING MANUFACTURING EFFICIENCY WITH DYNAMIC FIREFLY-TUNED ADABOOST APPROACH FOR TALL BUILDING DESIGN

The planning of tall buildings is an important part of urban growth, and more and more attention is being paid to sustainability, safety, and efficiency in the building process. Traditional design and manufacturing processes frequently have trouble maximizing these factors, which results in inefficiencies and higher prices. This research introduces a revolutionary strategy that combines dynamic firefly tuned-AdaBoost (DFT-AdaBoost) in order to address the drawbacks of conventional tall building design methodologies. The goal is to increase manufacturing efficiency while also enhancing the tall building design's sustainability and safety features. The DFO is employed in an iterative manner to modify various design parameters, including material types, sizes, and shapes. On the other hand, AdaBoosting is utilized to improve the predicted accuracy of the model. The iterative nature of this methodology enables the ongoing improvement of design solutions in order to get the necessary level of manufacturing efficiency. The findings of this study indicate notable enhancements in manufacturing efficacy pertaining to the construction of tall buildings. The utilization of the DFT-AdaBoost method enables the identification of optimized design parameters, resulting in the reduction of material waste and a decrease in production costs. This study highlights the DFT-AdaBoost approach's potential as a potent tool for improving manufacturing effectiveness in tall building designs. This method contributes to the construction of tall buildings that are more cost-effective, safe, and environmentally responsible by integrating real-time structural optimization with manufacturing process prediction.